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  • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
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  • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
  • C07K16/46—Hybrid immunoglobulins
  • C07K16/461—Igs containing Ig-regions, -domains or -residues form different species
  • C07K16/464—Igs containing CDR-residues from one specie grafted between FR-residues from another
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  • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
  • C07K14/475—Growth factors; Growth regulators
• • A—HUMAN NECESSITIES
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  • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
  • A61K47/00—Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additives; Targeting or modifying agents chemically bound to the active ingredient
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  • A61K47/06—Organic compounds, e.g. natural or synthetic hydrocarbons, polyolefins, mineral oil, petrolatum or ozokerite
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  • A61K47/12—Carboxylic acids; Salts or anhydrides thereof
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  • A61K9/00—Medicinal preparations characterised by special physical form
  • A61K9/70—Web, sheet or filament bases ; Films; Fibres of the matrix type containing drug
  • A61K9/7015—Drug-containing film-forming compositions, e.g. spray-on
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
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  • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
  • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
  • C07K14/52—Cytokines; Lymphokines; Interferons
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  • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
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  • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
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  • C07K16/28—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
  • C07K16/2866—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against receptors for cytokines, lymphokines, interferons
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  • C07K16/28—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
  • C07K16/2896—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants against molecules with a "CD"-designation, not provided for elsewhere
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  • C07—ORGANIC CHEMISTRY
  • C07K—PEPTIDES
  • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
  • C07K16/18—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
  • C07K16/28—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
  • C07K16/30—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells
• • C—CHEMISTRY; METALLURGY
  • C07—ORGANIC CHEMISTRY
  • C07K—PEPTIDES
  • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
  • C07K16/18—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans
  • C07K16/28—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
  • C07K16/30—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells
  • C07K16/3046—Stomach, Intestines
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
  • G16B15/00—ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
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  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
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  • G16B15/00—ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
  • G16B15/20—Protein or domain folding
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  • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
  • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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  • C07K—PEPTIDES
  • C07K2319/00—Fusion polypeptide

Definitions

• the present invention relates to polypeptides to be administered especially to humans and in particular for therapeutic use.
• the polypeptides are modified polypeptides whereby the modification results in a reduced propensity for the polypeptide to elicit an immune response upon administration to the human subject.
• the invention in particular relates to the modification of human keratinocyte growth factor (KGF) to result in KGF protein variants that are substantially non-immunogenic or less immunogenic than any non-modified counterpart when used in vivo.
• KGF human keratinocyte growth factor
• the invention relates furthermore to T-cell epitope peptides derived from said non-modified protein by means of which it is possible to create modified keratinocyte growth factor variants with reduced immunogenicity.
• Antibodies are not the only class of polypeptide molecule administered as a therapeutic agent against which an immune response may be mounted. Even proteins of human origin and with the same amino acid sequences as occur within humans can still induce an immune response in humans. Notable examples include the therapeutic use of granulocyte-macrophage colony stimulating factor [Wadhwa, M. et al (1999) Clin. Cancer Res . 5: 1353-1361] and interferon alpha 2 [Russo, D. et al (1996) Bri. J. Haem . 94: 300-305; Stein, R. et al (1988) New Engl. J. Med . 318: 1409-1413] amongst others.
• T-cell epitopes A principal factor in the induction of an immune response is the presence within the protein of peptides that can stimulate the activity of T-cell via presentation on MHC class II molecules, so-called “T-cell epitopes.
• T-cell epitopes are commonly defined as any amino acid residue sequence with the ability to bind to MHC Class II molecules.
• T-cell epitopes can be measured to establish MHC binding.
• a “T-cell epitope” means an epitope which when bound to MHC molecules can be recognized by a T-cell receptor (TCR), and which can, at least in principle, cause the activation of these T-cells by engaging a TCR to promote a T-cell response. It is, however, usually understood that certain peptides which are found to bind to MHC Class II molecules may be retained in a protein sequence because such peptides are recognized as “self” within the organism into which the final protein is administered.
• TCR T-cell receptor
• T-cell epitope peptides can be released during the degradation of peptides, polypeptides or proteins within cells and subsequently be presented by molecules of the major histocompatability complex (MHC) in order to trigger the activation of T-cells.
• MHC major histocompatability complex
• MHC Class II molecules are a group of highly polymorphic proteins which play a central role in helper T-cell selection and activation.
• the human leukocyte antigen group DR (HLA-DR) are the predominant isotype of this group of proteins and are the major focus of the present invention.
• isotypes HLA-DQ and HLA-DP perform similar functions, hence the resent invention is equally applicable to these.
• the MHC class II DR molecule is made of an alpha and a beta chain which insert at their C-termini through the cell membrane. Each hetero-dimer possesses a ligand binding domain which binds to peptides varying between 9 and 20 amino acids in length, although the binding groove can accommodate a maximum of 11 amino acids.
• the ligand binding domain is comprised of amino acids 1 to 85 of the alpha chain, and amino acids 1 to 94 of the beta chain.
• DQ molecules have recently been shown to have an homologous structure and the DP family proteins are also expected to be very similar. In humans approximately 70 different allotypes of the DR isotype are known, for DQ there are 30 different allotypes and for DP 47 different allotypes are known. Each individual bears two to four DR alleles, two DQ and two DP alleles.
• This polymorphism affects the binding characteristics of the peptide binding domain, thus different “families” of DR molecules will have specificities for peptides with different sequence properties, although there may be some overlap.
• This specificity determines recognition of Th-cell epitopes (Class II T-cell response) which are ultimately responsible for driving the antibody response to ⁇ -cell epitopes present on the same protein from which the Th-cell epitope is derived.
• Th-cell epitopes Class II T-cell response
• the immune response to a protein in an individual is heavily influenced by T-cell epitope recognition which is a function of the peptide binding specificity of that individual's HLA-DR allotype.
• An immune response to a therapeutic protein such as the protein which is object of this invention proceeds via the MHC class II peptide presentation pathway.
• exogenous proteins are engulfed and processed for presentation in association with MHC class II molecules of the DR, DQ or DP type.
• MHC Class II molecules are expressed by professional antigen presenting cells (APCs), such as macrophages and dendritic cells amongst others.
• APCs professional antigen presenting cells
• APCs professional antigen presenting cells
• Engagement of a MHC class II peptide complex by a cognate T-cell receptor on the surface of the T-cell, together with the cross-binding of certain other co-receptors such as the CD4 molecule, can induce an activated state within the T-cell. Activation leads to the release of cytokines further activating other lymphocytes such as B cells to produce antibodies or activating T killer cells as a full cellular immune response.
• the ability of a peptide to bind a given MHC class II molecule for presentation on the surface of an APC is dependent on a number of factors most notably its primary sequence. This will influence both its propensity for proteolytic cleavage and also its affinity for binding within the peptide binding cleft of the MHC class II molecule.
• the MHC class II/peptide complex on the APC surface presents a binding face to a particular T-cell receptor (TCR) able to recognize determinants provided both by exposed residues of the peptide and the MHC class II molecule.
• TCR T-cell receptor
• T-cell epitope identification is the first step to epitope elimination.
• the identification and removal of potential T-cell epitopes from proteins has been previously disclosed.
• methods have been provided to enable the detection of T-cell epitopes usually by computational means scanning for recognized sequence motifs in experimentally determined T-cell epitopes or alternatively using computational techniques to predict MHC class II-binding peptides and in particular DR-binding peptides.
• WO98/52976 and WO00/34317 teach computational threading approaches to identifying polypeptide sequences with the potential to bind a sub-set of human MHC class II DR allotypes.
• predicted T-cell epitopes are removed by the use of judicious amino acid substitution within the primary sequence of the therapeutic antibody or non-antibody protein of both non-human and human derivation.
• KGF keratinocyte growth factor
• FGF fibroblast growth factor
• heparin-binding growth factor family of proteins It is a secreted glycoprotein expressed predominantly in the lung, promoting wound healing by stimulating the growth of keratinocytes and other epithelial cells [Finch et al (1989), Science 24: 752-755; Rubin et al (1989), Proc. Natl. Acad. Sci. U.S.A. 86: 802-806].
• the mature (processed) form of the glycoprotein comprises 163 amino acid residues and may be isolated from conditioned media following culture of particular cell lines [Rubin et al, (1989) ibid.], or produced using recombinant techniques [Ron et al (1993) J. Biol. Chem. 268: 2984-2988].
• the protein is of therapeutic value for the stimulation of epithelial cell growth in a number of significant disease and injury repair settings.
• This disclosure specifically pertains the human KGF protein being the mature (processed) form of 163 amino acid residues.
• KGF molecules e.g. U.S. Pat. No. 6,008,328; WO90/08771;
• modified KGF Non et al (1993) ibid; WO9501434.
• KGF keratinocyte growth factor
• KGF keratinocyte growth factor
• Desired enhancements include alternative schemes and modalities for the expression and purification of the said therapeutic, but also and especially, improvements in the biological properties of the protein.
• KGF keratinocyte growth factor
• the present invention provides for modified forms of “keratinocyte growth factor (KGF)”, in which the immune characteristic is modified by means of reduced or removed numbers of potential T-cell epitopes.
• the present invention provides for modified forms of human keratinocyte growth factor (KGF) with one or more T-cell epitopes removed.
• KGF proteins such as identified from other mammalian or vertebrate sources have in common many of the peptide sequences of the present disclosure and have in common many peptide sequences with substantially the same sequence as those of the disclosed listing. Such protein sequences equally therefore fall under the scope of the present invention.
• the invention discloses sequences identified within the keratinocyte growth factor primary sequence that are potential T-cell epitopes by virtue of MHC class II binding potential. This disclosure specifically pertains the human KGF protein being the 163 amino acid residues.
• the invention discloses also specific positions within the primary sequence of the molecule according to the invention which has to be altered by specific amino acid substitution, addition or deletion without affecting the biological activity in principal. In cases in which the loss of immunogenicity can be achieved only by a simultaneous loss of biological activity it is possible to restore said activity by further alterations within the amino acid sequence of the protein.
• the invention discloses furthermore methods to produce such modified molecules, above all methods to identify said T-cell epitopes which have to be altered in order to reduce or remove immunogenetic sites.
• the invention may be-applied to any KGF species of molecule with substantially the same primary amino acid sequences as those disclosed herein and would include therefore KGF molecules derived by genetic engineering means or other processes and may not contain 163 amino acid residues.
• the protein according to this invention would expect to display an increased circulation time within the human subject and would be of particular benefit in chronic or recurring disease settings such as is the case for a number of indications for keratinocyte growth factor (KGF).
• KGF keratinocyte growth factor
• the present invention provides for modified forms of KGF proteins that are expected to display enhanced properties in vivo. These modified KGF molecules can be used in pharmaceutical compositions.
• a modified molecule having the biological activity of keratinocyte growth factor (KGF) and being substantially non-immunogenic or less immunogenic than any non-modified molecule having the same biological activity when used in vivo;
• KGF keratinocyte growth factor
• an accordingly specified molecule wherein said loss of immunogenicity is achieved by removing one or more T-cell epitopes derived from the originally non-modified molecule;
• T-cell epitopes are MHC class II ligands or peptide sequences which show the ability to stimulate or bind T-cells via presentation on class II;
• an accordingly specified molecule wherein 1-9 amino acid residues, preferably one amino acid residue in any of the originally present T-cell epitopes are altered;
• an accordingly specified molecule wherein, if necessary, additionally further alteration usually by substitution, addition or deletion of specific amino acid(s) is conducted to restore biological activity of said molecule;
• a pharmaceutical composition comprising a modified molecule having the biological activity of keratinocyte growth factor (KGF) as defined above and/or in the claims, optionally together with a pharmaceutically acceptable carrier, diluent or excipient;
• KGF keratinocyte growth factor
• a method for manufacturing a modified molecule having the biological activity of keratinocyte growth factor (KGF) as defined in any of the claims of the above-cited claims comprising the following steps: (i) determining the amino acid sequence of the polypeptide or part thereof; (ii) identifying one or more potential T-cell epitopes within the amino acid sequence of the protein by any method including determination of the binding of the peptides to MHC molecules using in vitro or in silico techniques or biological assays; (iii) designing new sequence variants with one or more amino acids within the identified potential T-cell epitopes modified in such a way to substantially reduce or eliminate the activity of the T-cell epitope as determined by the binding of the peptides to MHC molecules using in vitro or in silico techniques or biological assays; (iv) constructing such sequence variants by recombinant DNA techniques and testing said variants in order to identify one or more variants with desirable properties; and (v) optionally repeating steps (ii)-
• step (iii) is carried out by substitution, addition or deletion of 1-9 amino acid residues in any of the originally present T-cell epitopes;
• step (ii) of above is carried out by the following steps: (a) selecting a region of the peptide having a known amino acid residue sequence; (b) sequentially sampling overlapping amino acid residue segments of predetermined uniform size and constituted by at least three amino acid residues from the selected region; (c) calculating MHC Class II molecule binding score for each said sampled segment by summing assigned values for each hydrophobic amino acid residue side chain present in said sampled amino acid residue segment; and (d) identifying at least one of said segments suitable for modification, based on the calculated MHC Class II molecule binding score for that segment, to change overall MHC Class II binding score for the peptide without substantially reducing therapeutic utility of the peptide; step (c) is preferably carried out by using a Böhm scoring function modified to include 12-6 van der Waal's ligand-protein energy repulsive term and ligand conformational energy term by (1) providing a first data base of MHC Class II molecule models; (2) providing a second
• KGF immunogenetically non-modified keratinocyte growth factor
• a peptide sequence consisting of at least 9 consecutive amino acid residues of a 13 mer T-cell epitope peptide as specified above and its use for the manufacture of KGF having substantially no or less immunogenicity than any non-modified molecule with the same biological activity when used in vivo;
• T-cell epitope means according to the understanding of this invention an amino acid sequence which is able to bind MCH II, able to stimulate T-cells and/or also to bind (without necessarily measurably activating) T-cells in complex with MHC II.
• peptide as used herein and in the appended claims, is a compound that includes two or more amino acids. The amino acids are linked together by a peptide bond (defined herein below). There are 20 different naturally occurring amino acids involved int eh biological production of peptides, and any number of them may be linked in any order to form a peptide chain or ring. The naturally occurring amino acids employed in the biological production of peptides all have the L-configuration.
• Synthetic peptides can be prepared employing conventional synthetic methods, utilizing L-amino acids, D-amino acids, or various combinations of amino acids of the two different configurations. Some peptides contain only a few amino acid units. Short peptides, e.g., having less than ten amino acid units, are sometimes referred to as “oligopeptides”. Other peptides contain a large number of amino acid residues, e.g. up to 100 ore more, and are referred to as “polypeptides”. By convention, a “polypeptide” may be considered as any peptide chain containing three or more amino acids, whereas a “oligopeptide” is usually considered as a particular type of “short” polypeptide.
• any reference to a “polypeptide” also includes an oligopeptide.
• any reference to a “peptide” includes polypeptides, oligopeptides, and proteins. Each different arrangement of amino acids forms different polypeptides or proteins. The number of polypeptides—and hence the number of different proteins—that can be formed is practically unlimited.
• “Alpha carbon (C ⁇ )” is the carbon atom of the carbon-hydrogen (CH) component that is in the peptide chain.
• a “side chain” is a pendant group to C ⁇ that can comprise a simple or complex group or moiety, having physical dimensions that can vary significantly compared to the dimensions of the peptide.
• the invention may be applied to any keratinocyte growth factor (KGF) species of molecule with substantially the same primary amino acid sequences as those disclosed herein and would include therefore keratinocyte growth factor (KGF) molecules derived by genetic engineering means or other processes and may not contain either 163 amino acid residues.
• KGF keratinocyte growth factor
• Keratinocyte growth factor (KGF) proteins such as identified from other mammalian sources have in common many of the peptide sequences of the present disclosure and have in common many peptide sequences with substantially the same sequence as those of the disclosed listing. Such protein sequences equally therefore fall under the scope of the present invention.
• the invention is conceived to overcome the practical reality that soluble proteins introduced into autologous organisms can trigger an immune response resulting in development of host antibodies that bind to the soluble protein.
• KGF keratinocyte growth factor
• the present invention seeks to address this by providing keratinocyte growth factor (KGF) proteins with altered propensity to elicit an immune response on administration to the human host.
• the general method of the present invention leading to the modified keratinocyte growth factor (KGF) comprises the following steps:
• step (b) The identification of potential T-cell epitopes according to step (b) can be carried out according to methods describes previously in the prior art. Suitable methods are disclosed in WO 98/59244; WO 98/52976; WO 00/34317 and may preferably be used to identify binding propensity of keratinocyte growth factor (KGF)-derived peptides to an MHC class II molecule.
• KGF keratinocyte growth factor
• KGF keratinocyte growth factor
• NDMTPEQMATNVN DMTPEQMATNVNC, EQMATNVNCSSPE, TNVNCSSPERHTR, RSYDYMEGGDIRV, YDYMEGGDIRVRR, DYMEGGDIRVRRL, GDIRVRRLFCRTQ, IRVRRLFCRTQWY, RRLFCRTQWYLRI, RLFCRTQWYLRID, TQWYLRIDKRGKV, QWYLRIDKRGKVK, WYLRIDKRGKVKG, LRIDKRGKVKGTQ, GKVKGTQEMKNNY, QEMKNNYNIMEIR, NNYNIMEIRTVAV, YNIMEIRTVAVGI, NIMEIRTVAVGIV, MEIRTVAVGIVAI, RTVAVGIVAIKGV, VAVGIVAIKGVES, VGIVAIKGVESEF, VAIKGVESEFYLA, KGVESEFYLAMNKEGKL, EFYLAM
• Peptides are 13 mers, amino acids are identified using single letter code.
• the invention relates to keratinocyte growth factor (KGF) analogues in which substitutions of at least one amino acid residue have been made at positions resulting in a substantial reduction in activity of or elimination of one or more potential T-cell epitopes from the protein.
• KGF keratinocyte growth factor
• One or more amino acid substitutions at particular points within any of the potential MHC class II ligands identified in Table 1 may result in a keratinocyte growth factor (KGF) molecule with a reduced immunogenic potential when administered as a therapeutic to the human host.
• amino acid substitutions are made at appropriate points within the peptide sequence predicted to achieve substantial reduction or elimination of the activity of the T-cell epitope. In practice an appropriate point will preferably equate to an amino acid residue binding within one of the hydrophobic pockets provided within the MHC class II binding groove.
• Amino acid substitutions other than within the peptides identified above may be contemplated particularly when made in combination with substitution(s) made within a listed peptide.
• a change may be contemplated to restore structure or biological activity of the variant molecule.
• Such compensatory changes and changes to include deletion or addition of particular amino acid residues from the keratinocyte growth factor (KGF) polypeptide resulting in a variant with desired activity and in combination with changes in any of the disclosed peptides fall under the scope of the present.
• KGF keratinocyte growth factor
• modified keratinocyte growth factor KGF
• compositions containing such modified keratinocyte growth factor (KGF) proteins or fragments of modified keratinocyte growth factor (KGF) proteins and related compositions should be considered within the scope of the invention.
• the present invention relates to nucleic acids encoding modified keratinocyte growth factor (KGF) entities.
• the present invention relates to methods for therapeutic treatment of humans using the modified keratinocyte growth factor (KGF) proteins.
• the peptide bond i.e., that bond which joins the amino acids in the chain together, is a covalent bond.
• This bond is planar in structure, essentially a substituted amide.
• An “amide” is any of a group of organic compounds containing the grouping —CONH—.
• planar peptide bond linking C ⁇ of adjacent amino acids may be represented as depicted below:
• a second factor that plays an important role in defining the total structure or conformation of a polypeptide or protein is the angle of rotation of each amide plane about the common C ⁇ linkage.
• angle of rotation and “torsion angle” are hereinafter regarded as equivalent terms. Assuming that the O, C, N, and H atoms remain in the amide plane (which is usually a valid assumption, although there may be some slight deviations from planarity of these atoms for some conformations), these angles of rotation define the N and R polypeptide's backbone conformation, i.e., the structure as it exists between adjacent residues. These two angles are known as ⁇ and ⁇ .
• the present method can be applied to any protein, and is based in part upon the discovery that in humans the primary Pocket 1 anchor position of MHC Class II molecule binding grooves has a well designed specificity for particular amino acid side chains.
• the specificity of this pocket is determined by the identity of the amino acid at position 86 of the beta chain of the MHC Class II molecule. This site is located at the bottom of Pocket 1 and determines the size of the side chain that can be accommodated by this pocket. Marshall, K. W., J. Immunol ., 152:4946-4956 (1994).
• this residue is a glycine
• all hydrophobic aliphatic and aromatic amino acids hydrophobic aliphatics being: valine, leucine, isoleucine, methionine and aromatics being: phenylalanine, tyrosine and tryptophan
• this pocket residue is a valine
• the side chain of this amino acid protrudes into the pocket and restricts the size of peptide side chains that can be accommodated such that only hydrophobic aliphatic side chains can be accommodated.
• a computational method embodying the present invention profiles the likelihood of peptide regions to contain T-cell epitopes as follows:
• hydrophobic aliphatic side chains are assigned a value greater than that for the aromatic side chains; preferably about twice the value assigned to the aromatic side chains, e.g., a value of 2 for a hydrophobic aliphatic side chain and a value of 1 for an aromatic side chain.
• T-cell epitopes can be predicted with greater accuracy by the use of a more sophisticated computational method which takes into account the interactions of peptides with models of MHC Class II alleles.
• the computational prediction of T-cell epitopes present within a peptide contemplates the construction of models of at least 42 MHC Class II alleles based upon the structures of all known MHC Class II molecules and a method for the use of these models in the computational identification of T-cell epitopes, the construction of libraries of peptide backbones for each model in order to allow for the known variability in relative peptide backbone alpha carbon (C ⁇ ) positions, the construction of libraries of amino-acid side chain conformations for each backbone dock with each model for each of the 20 amino-acid alternatives at positions critical for the interaction between peptide and MHC Class II molecule, and the use of these libraries of backbones and side-chain conformations in conjunction with a scoring function to select the optimum backbone and side-
• Models of MHC Class II molecules can be derived via homology modeling from a number of similar structures found in the Brookhaven Protein Data Bank (“PDB”). These may be made by the use of semi-automatic homology modeling software (Modeller, Sali A. & Blundell T L., 1993 . J. Mol Biol 234:779-815) which incorporates a simulated annealing function, in conjunction with the CHARMm force-field for energy minimisation (available from Molecular Simulations Inc., San Diego, Calif.). Alternative modeling methods can be utilized as well.
• PDB Brookhaven Protein Data Bank
• the present method differs significantly from other computational methods which use libraries of experimentally derived binding data of each amino-acid alternative at each position in the binding groove for a small set of MHC Class II molecules (Marshall, K. W., et al., Biomed. Pept. Proteins Nucleic Acids , 1(3):157-162) (1995) or yet other computational methods which use similar experimental binding data in order to define the binding characteristics of particular types of binding pockets within the groove, again using a relatively small subset of MHC Class II molecules, and then ‘mixing and matching’ pocket types from this pocket library to artificially create further ‘virtual’ MHC Class II molecules (Sturniolo T., et al., Nat. Biotech , 17(6): 555-561 (1999).
• Both prior methods suffer the major disadvantage that, due to the complexity of the assays and the need to synthesize large numbers of peptide variants, only a small number of MHC Class II molecules can be experimentally scanned. Therefore the first prior method can only make predictions for a small number of MHC Class II molecules.
• the second prior method also makes the assumption that a pocket lined with similar amino-acids in one molecule will have the same binding characteristics when in the context of a different Class II allele and suffers further disadvantages in that only those MHC Class II molecules can be ‘virtually’ created which contain pockets contained within the pocket library.
• the structure of any number and type of MHC Class II molecules can be deduced, therefore alleles can be specifically selected to be representative of the global population.
• the number of MHC Class II molecules scanned can be increased by making further models further than having to generate additional data via complex experimentation.
• the present backbone library is created by superposing the backbones of all peptides bound to MHC Class II molecules found within the Protein Data Bank and noting the root mean square (RMS) deviation between the C ⁇ atoms of each of the eleven amino-acids located within the binding groove. While this library can be derived from a small number of suitable available mouse and human structures (currently 13), in order to allow for the possibility of even greater variability, the RMS figure for each C′′- ⁇ position is increased by 50%. The average C ⁇ position of each amino-acid is then determined and a sphere drawn around this point whose radius equals the RMS deviation at that position plus 50%. This sphere represents all allowed C ⁇ positions.
• RMS root mean square
• the sphere is three-dimensionally gridded, and each vertex within the grid is then used as a possible location for a C ⁇ of that amino-acid.
• the subsequent amide plane, corresponding to the peptide bond to the subsequent amino-acid is grafted onto each of these C ⁇ s and the ⁇ and ⁇ angles are rotated step-wise at set intervals in order to position the subsequent C ⁇ . If the subsequent C ⁇ falls within the ‘sphere of allowed positions’ for this C ⁇ than the orientation of the dipeptide is accepted, whereas if it falls outside the sphere then the dipeptide is rejected.
• This process is then repeated for each of the subsequent C ⁇ positions, such that the peptide grows from the Pocket 1 C ⁇ ‘seed’, until all nine subsequent C ⁇ s have been positioned from all possible permutations of the preceding C ⁇ s.
• the process is then repeated once more for the single C ⁇ preceding pocket 1 to create a library of backbone C ⁇ positions located within the binding groove.
• the number of backbones generated is dependent upon several factors: The size of the ‘spheres of allowed positions’; the fineness of the gridding of the ‘primary sphere’ at the Pocket 1 position; the fineness of the step-wise rotation of the ⁇ and ⁇ angles used to position subsequent C ⁇ s. Using this process, a large library of backbones can be created.
• backbone library The larger the backbone library, the more likely it will be that the optimum fit will be found for a particular peptide within the binding groove of an MHC Class II molecule. Inasmuch as all backbones will not be suitable for docking with all the models of MHC Class II molecules due to clashes with amino-acids of the binding domains, for each allele a subset of the library is created comprising backbones which can be accommodated by that allele.
• the use of the backbone library, in conjunction with the models of MHC Class II molecules creates an exhaustive database consisting of allowed side chain conformations for each amino-acid in each position of the binding groove for each MHC Class II molecule docked with each allowed backbone.
• This data set is generated using a simple steric overlap function where a MHC Class II molecule is docked with a backbone and an amino-acid side chain is grafted onto the backbone at the desired position.
• Each of the rotatable bonds of the side chain is rotated step-wise at set intervals and the resultant positions of the atoms dependent upon that bond noted.
• the interaction of the atom with atoms of side-chains of the binding groove is noted and positions are either accepted or rejected according to the following criteria:
• the sum total of the overlap of all atoms so far positioned must not exceed a pre-determined value.
• the stringency of the conformational search is a function of the interval used in the step-wise rotation of the bond and the pre-determined limit for the total overlap.
• a suitable mathematical expression is used to estimate the energy of binding between models of MHC Class II molecules in conjunction with peptide ligand conformations which have to be empirically derived by scanning the large database of backbone/side-chain conformations described above.
• a protein is scanned for potential T-cell epitopes by subjecting each possible peptide of length varying between 9 and 20 amino-acids (although the length is kept constant for each scan) to the following computations:
• An MHC Class II molecule is selected together with a peptide backbone allowed for that molecule and the side-chains corresponding to the desired peptide sequence are grafted on.
• Atom identity and interatomic distance data relating to a particular side-chain at a particular position on the backbone are collected for each allowed conformation of that amino-acid (obtained from the database described above). This is repeated for each side-chain along the backbone and peptide scores derived using a scoring function. The best score for that backbone is retained and the process repeated for each allowed backbone for the selected model. The scores from all allowed backbones are compared and the highest score is deemed to be the peptide score for the desired peptide in that MHC Class II model. This process is then repeated for each model with every possible peptide derived from the protein being scanned, and the scores for peptides versus models are displayed.
• each ligand presented for the binding affinity calculation is an amino-acid segment selected from a peptide or protein as discussed above.
• the ligand is a selected stretch of amino acids about 9 to 20 amino acids in length derived from a peptide, polypeptide or protein of known sequence.
• amino acids and “residues” are hereinafter regarded as equivalent terms.
• the ligand in the form of the consecutive amino acids of the peptide to be examined grafted onto a backbone from the backbone library, is positioned in the binding cleft of an MHC Class II molecule from the MHC Class II molecule model library via the coordinates of the C′′- ⁇ atoms of the peptide backbone and an allowed conformation for each side-chain is selected from the database of allowed conformations.
• the relevant atom identities and interatomic distances are also retrieved from this database and used to calculate the peptide binding score.
• Ligands with a high binding affinity for the MHC Class II binding pocket are flagged as candidates for site-directed mutagenesis.
• Amino-acid substitutions are made in the flagged ligand (and hence in the protein of interest) which is then retested using the scoring function in order to determine changes which reduce the binding affinity below a predetermined threshold value. These changes can then be incorporated into the protein of interest to remove T-cell epitopes. Binding between the peptide ligand and the binding groove of MHC Class II molecules involves non-covalent interactions including, but not limited to: hydrogen bonds, electrostatic interactions, hydrophobic (lipophilic) interactions and Van der Walls interactions. These are included in the peptide scoring function as described in detail below.
• a hydrogen bond is a non-covalent bond which can be formed between polar or charged groups and consists of a hydrogen atom shared by two other atoms.
• the hydrogen of the hydrogen donor has a positive charge where the hydrogen acceptor has a partial negative charge.
• hydrogen bond donors may be either nitrogens with hydrogen attached or hydrogens attached to oxygen or nitrogen.
• Hydrogen bond acceptor atoms may be oxygens not attached to hydrogen, nitrogens with no hydrogens attached and one or two connections, or sulphurs with only one connection.
• Certain atoms, such as oxygens attached to hydrogens or imine nitrogens may be both hydrogen acceptors or donors.
• Hydrogen bond energies range from 3 to 7 Kcal/mol and are much stronger than Van der Waal's bonds, but weaker than covalent bonds. Hydrogen bonds are also highly directional and are at their strongest when the donor atom, hydrogen atom and acceptor atom are co-linear. Electrostatic bonds are formed between oppositely charged ion pairs and the strength of the interaction is inversely proportional to the square of the distance between the atoms according to Coulomb's law. The optimal distance between ion pairs is about 2.8 ⁇ . In protein/peptide interactions, electrostatic bonds may be formed between arginine, histidine or lysine and aspartate or glutamate.
• the strength of the bond will depend upon the pKa of the ionizing group and the dielectric constant of the medium although they are approximately similar in strength to hydrogen bonds. Lipophilic interactions are favorable hydrophobic-hydrophobic contacts that occur between he protein and peptide ligand. Usually, these will occur between hydrophobic amino acid side chains of the peptide buried within the pockets of the binding groove such that they are not exposed to solvent. Exposure of the hydrophobic residues to solvent is highly unfavorable since the surrounding solvent molecules are forced to hydrogen bond with each other forming cage-like clathrate structures. The resultant decrease in entropy is highly unfavorable.
• Lipophilic atoms may be sulphurs which are neither polar nor hydrogen acceptors and carbon atoms which are not polar.
• Van der Waal's bonds are non-specific forces found between atoms which are 3-4 ⁇ apart. They are weaker and less specific than hydrogen and electrostatic bonds.
• the distribution of electronic charge around an atom changes with time and, at any instant, the charge distribution is not symmetric. This transient asymmetry in electronic charge induces a similar asymmetry in neighboring atoms.
• the resultant attractive forces between atoms reaches a maximum at the Van der Waal's contact distance but diminishes very rapidly at about 1 ⁇ to about 2 ⁇ .
• the Böhm scoring function (SCORE1 approach) is used to estimate the binding constant. (Böhm, H. J., J. Comput Aided Mol. Des ., 8(3):243-256 (1994) which is hereby incorporated in its entirety).
• the scoring function (SCORE2 approach) is used to estimate the binding affinities as an indicator of a ligand containing a T-cell epitope (Böhm, H. J., J. Comput Aided Mol. Des ., 12(4):309-323 (1998) which is hereby incorporated in its entirety).
• the Böhm scoring functions as described in the above references are used to estimate the binding affinity of a ligand to a protein where it is already known that the ligand successfully binds to the protein and the protein/ligand complex has had its structure solved, the solved structure being present in the Protein Data Bank (“PDB”). Therefore, the scoring function has been developed with the benefit of known positive binding data In order to allow for discrimination between positive and negative binders, a repulsion term must be added to the equation. In addition, a more satisfactory estimate of binding energy is achieved by computing the lipophilic interactions in a pairwise manner rather than using the area based energy term of the above Böhm functions. Therefore, in a preferred embodiment, the binding energy is estimated using a modified Böhm scoring function.
• the binding energy between protein and ligand ( ⁇ G bind ) is estimated considering the following parameters: The reduction of binding energy due to the overall loss of translational and rotational entropy of the ligand ( ⁇ G 0 ); contributions from ideal hydrogen bonds ( ⁇ G hb ) where at least one partner is neutral; contributions from unperturbed ionic interactions ( ⁇ G ionic ); lipophilic interactions between lipophilic ligand atoms and lipophilic acceptor atoms ( ⁇ G lipo ); the loss of binding energy due to the freezing of internal degrees of freedom in the ligand, i.e., the freedom of rotation about each C—C bond is reduced ( ⁇ G rot ); the energy of the interaction between the protein and ligand (E VdW ). Consideration of these terms gives equation 1:
• N is the number of qualifying interactions for a specific term and, in one embodiment, ⁇ G 0 , ⁇ G hb , ⁇ G ionic , ⁇ G lipo and ⁇ G rot are constants which are given the values: 5.4, ⁇ 4.7, ⁇ 4.7, ⁇ 0.17, and 1.4, respectively.
• N hb is calculated according to equation 2:
• N hb ⁇ h-bonds f ( ⁇ R , ⁇ ) ⁇ f ( N neighb ) ⁇ f pcs
• ⁇ is the deviation of the hydrogen bond angle ⁇ N/O—H..O/N from its idealized value of 180°
• f(N neighb ) distinguishes between concave and convex parts of a protein surface and therefore assigns greater weight to polar interactions found in pockets rather than those found at the protein surface. This function is calculated according to equation 4 below:
• N neighb is the number of non-hydrogen protein atoms that are closer than 5 ⁇ to any given protein atom.
• f pcs is a function which allows for the polar contact surface area per hydrogen bond and therefore distinguishes between strong and weak hydrogen bonds and its value is determined according to the following criteria:
• a polar is the size of the polar protein-ligand contact surface
• N HB is the number of hydrogen bonds
• N lipo is calculated according to equation 5 below:
• N lipo ⁇ lL f ( r lL )
• f(r lL ) is calculated for all lipophilic ligand atoms, l, and all lipophilic protein atoms, L, according to the following criteria:
• r l vdw is the Van der Waal's radius of atom l
• N rot is the number of rotable bonds of the amino acid side chain and is taken to be the number of acyclic sp 3 -sp 3 and sp 3 -sp 2 bonds. Rotations of terminal —CH 3 or —NH 3 are not taken into account.
• ⁇ 1 and ⁇ 2 are constants dependant upon atom identity
• r 1 vdw +r 2 vdw are the Van der Waal's atomic radii
• r is the distance between a pair of atoms.
• the constants ⁇ 1 and ⁇ 2 are given the atom values: C, 0.245; N, 0.283; O, 0.316; S, 0.316; respectively (i.e. for atoms of Carbon, Nitrogen, Oxygen and Sulphur, respectively).
• the Van der Waal's radii are given the atom values C, 1.85; N, 1.75; O, 1.60, S, 2.00 ⁇ .
• the scoring function is applied to data extracted from the database of side-chain conformations, atom identities, and interatomic distances.
• the number of MHC Class II molecules included in this database is 42 models plus four solved structures.
• the present prediction method can be calibrated against a data set comprising a large number of peptides whose affinity for various MHC Class II molecules has previously been experimentally determined. By comparison of calculated versus experimental data, a cut of value can be determined above which it is known that all experimentally determined T-cell epitopes are correctly predicted.
• Examples of molecular modeling and manipulation software include: AMBER (Tripos) and CHARMm (Molecular Simulations Inc.).
• AMBER Tripos
• CHARMm Molecular Simulations Inc.
• the use of these computational methods would severely limit the throughput of the method of this invention due to the lengths of processing time required to make the necessary calculations.
• it is feasible that such methods could be used as a ‘secondary screen’ to obtain more accurate calculations of binding energy for peptides which are found to be ‘positive binders’ via the method of the present invention.
• the limitation of processing time for sophisticated molecular mechanic or molecular dynamic calculations is one which is defined both by the design of the software which makes these calculations and the current technology limitations of computer hardware.

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